# Define Panel visualization functions
def neighbourhood_map():
"""Neighbourhood Map"""
# YOUR CODE HERE!
api_token="pk.eyJ1Ijoic2lkZGhkb3NpIiwiYSI6ImNreGVudnpnNjA3NXcycG54bXF4MmRodzMifQ.8yVH47iUqi6nwLQR_LUB1g"
px.set_mapbox_access_token(api_token)
avg_by_neighbourhood = to_data.groupby(['neighbourhood']).mean().reset_index()
neighbourhood_df = pd.merge(df_neighbourhood_locations,avg_by_neighbourhood,on='neighbourhood',how='inner')
fig = px.scatter_mapbox(neighbourhood_df, lat="lat", lon="lon", color="average_house_value", size="average_house_value",
color_continuous_scale=px.colors.cyclical.IceFire,height=400,width=800,title='Averange House Values in Toronto')
return fig
def create_bar_chart(data, title, xlabel, ylabel, color):
"""
Create a barplot based in the data argument.
"""
# YOUR CODE HERE!
fig = plt.figure(figsize=(5,3))
plt.bar(data.index, data.values, color =color)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
plt.xticks(rotation=90)
plt.close(fig)
return fig
def create_line_chart(data, title, xlabel, ylabel, color):
"""
Create a line chart based in the data argument.
"""
# YOUR CODE HERE!
fig = plt.figure()
plt.plot(data.index,data.values,color=color)
plt.xlabel(xlabel)
plt.ylabel(ylabel)
plt.title(title)
plt.close(fig)
return fig
def average_house_value():
"""Average house values per year."""
# YOUR CODE HERE!
avg_house_val_per_yr = to_data[['average_house_value']].groupby(['year']).mean()
fig = create_line_chart(avg_house_val_per_yr['average_house_value'],
'Average House Value in Toronto',
'Year', 'Avg House Value', color='blue')
return fig
def average_value_by_neighbourhood():
"""Average house values by neighbourhood."""
# YOUR CODE HERE!
avg_house_val_by_neighbourhood = to_data[['neighbourhood','average_house_value']].groupby(['year','neighbourhood']).mean().reset_index()
fig = avg_house_val_by_neighbourhood.hvplot(x='year',y='average_house_value',kind='line',groupby='neighbourhood')
return fig
def number_dwelling_types():
"""Number of dwelling types per year"""
num_dwelling_type_by_neighbourhood = to_data.groupby(['year','neighbourhood']).sum().reset_index()
dwelling_type_col = ['single_detached_house',
'apartment_five_storeys_plus',
'movable_dwelling','semi_detached_house',
'row_house', 'duplex', 'apartment_five_storeys_less', 'other_house']
fig = num_dwelling_type_by_neighbourhood.hvplot(x='year',y=dwelling_type_col,
kind='bar',groupby='neighbourhood',
rot=90,xlabel='Year',ylabel='Dwelling Type Units',width=650,height=500)
return fig
def average_house_value_snapshot():
"""Average house value for all Toronto's neighbourhoods per year."""
# YOUR CODE HERE!
avg_house_val_by_neighbourhood = to_data[['neighbourhood','average_house_value']].groupby(['year','neighbourhood']).mean().reset_index()
fig = px.bar(avg_house_val_by_neighbourhood, x="neighbourhood", y="average_house_value",
color='average_house_value', facet_row="year",
height=1000,width=900,
title='Avgrage House Value per Neighbourhood')
return fig
def top_most_expensive_neighbourhoods():
"""Top 10 most expensive neighbourhoods."""
# YOUR CODE HERE!
top_10_expensive_neighbourhoods = to_data.groupby(['neighbourhood']).mean().reset_index().sort_values(by=['average_house_value'],ascending=False).head(10).reset_index(drop=True)
fig = top_10_expensive_neighbourhoods.hvplot(x='neighbourhood',y='average_house_value',
xlabel='Neighbourhood',ylabel='Avg. House Value',title = 'Top 10 Expensive Neighbourhood in Toronto',
rot=90,kind='bar',width=650,height=500)
return fig
def sunburts_cost_analysis():
"""Sunburst chart to conduct a costs analysis of most expensive neighbourhoods in Toronto per year."""
# YOUR CODE HERE!
filter_df = to_data[to_data.neighbourhood.isin(top_10_expensive_neighbourhoods.neighbourhood)]
most_expensive_neighbourhood_per_year = filter_df.groupby(['year','neighbourhood']).sum().reset_index()
fig = px.sunburst(most_expensive_neighbourhood_per_year, path=['year', 'neighbourhood'], values='shelter_costs_owned',
color='shelter_costs_owned',
color_continuous_scale='RdBu',
color_continuous_midpoint=np.average(most_expensive_neighbourhood_per_year['shelter_costs_owned'], weights=most_expensive_neighbourhood_per_year['shelter_costs_owned'])
,height=600,width=800,title='Cost Analysis of Most Expensive Neighbourhoods in Toronto per Year')
return fig
